Forecast Investigator

1. Click and then Investigator.

2. The default selection is Pricing. Click the drop down and select to investigate my Forecast.

• By default, all Forecast Groups, Room Classes, and days of the week display. Change the filters to drill down.
• For a specific Room Class, switch between Booked and Stayed data. Review a scenario or learn more about Booked and Stayed data.
• If needed, click Export to save the results to an Excel spreadsheet.
  Note: use this option to see ADR data (available only for Stayed data).
• Click to Compare Periods side by side. 
  For example, compare business for this year’s April against April of the past two years.
   
  1. For the current period, enter the Analysis Start Date and Analysis End Date.
  2. Enter the start dates for up to two Comparison periods. They have the same duration as the Analysis period.
  3. Click Apply. The chart displays the defined periods, separated by a blue dotted line.
  4. Click to remove the comparison and see all data.

Interacting with the Graphs

• Point to a line to see numerical values.
• To view a period in more detail, click and drag over that area of the chart. Click Reset zoom to reset the view.
• Click an item in the legend to hide the item from the chart. Click it again to restore it.

Review the graph details

1. On the At a Glance Dashboard, review high-level information:

   • Check the calendar for dates when the forecast doesn't align with what you know

   • Use the heat map to check the day of week demand pattern. Are there any outliers that you need to investigate? These might be indicators of Special Events that you need to share.

   • If needed, click a date to review past performance, price, and other decisions.

   • Below the calendar, use the Summary table to check your expectations of key metrics for the whole month. Compare to relevant past performance, for example, same time last year (STYL).

2. On the Business Analysis Data Details page, drill down to review the business mix.

   • Review the Occupancy Forecast at the Group and Transient level.
   • Compare On Books against remaining demand and against the same time in previous years.
   • When your forecast expectations don't align with the system's, view the transient data by Forecast Group. Focus on your largest Forecast Groups.
     Note the limitations about reviewing at market segment level.

3. Use the Forecast Investigator to help you understand patterns and trends.

Comparing the forecast and pace to previous years might be misleading because G3 RMS weighs whether to use recent past or previous years for its forecast. The Investigator can help you determine if the system favors recent or distant past. See this scenario.

1. Use the Business Analysis Summary to review Pricing, LRV, and Overbooking by month.

2. The Pricing Investigator helps you to see what impacts the price like demand, LRV, competitors, etc.

3. Review the Overbooking page to investigate Wash, individual groups, or configuration.

1. Continue to monitor, override, add Special Events, or change your configuration.

G3 RMS uses past occupancy data by Forecast Group and Room Class to understand how much unconstrained demand existed. And the system uses that historical demand in its demand calculation, see this video for details. Use the graph to: 

G3 RMS collects your property's demand history to calculate unconstrained demand by Forecast Group and Room Class. Then the system uses that data to forecast future unconstrained demand. Use the graph to:

1. Look for trends in the Occupancy On Books (blue line) of the past and compare this to the future System Total Demand (green line).
2. Look for dramatic increases or decreases and ask questions about what the cause might be.
   For example, an occupancy drop might be due to a higher price (visible in the ADR of the Excel export).
   
3. Begin with All Forecast Groups and All Room Classes.l. Then drill down to Forecast Groups. Focus on the larger ones that make up the majority of your business and are likely to impact the overall property trends.
4. Look for unusual trends for a specific Forecast Group, making sure you know the included market segments and their attributes. Are individual market segments causing the unusual trends?
5. If needed, check if the trends vary by Room Class. If available, switch and compare Booked and Stayed data to see upgrade patterns. If you are unsure if G3 RMS uses Booked or Stayed data, click Important Information .

Review the scenarios for detailed examples.

On the date that you set for when patterns are normal, G3 RMS starts using Actuals The occupancy, revenue or ADR that the property achieved, once the day is in the past. Actual occupancy is also called Final Rooms Sold. to forecast demand. Ensure that date is correct by checking that the following patterns match your expectations for business going forward. Start at the property level, then drill down to your biggest Forecast Groups:

• Volume of business: Is the Occupancy On Books since opening date still increasing or is it consistent?

• Business mix: compare the volumes of your biggest Forecast Groups against the property level - is their share as expected?.

• Pace: Is the Occupancy On Books for one week, two weeks, etc. after the selected date what you expect?

• Day of week patterns: are the occupancy patterns consistent?

• ADR: export the data to review. For example, are introductory discounted offers impacting the ADR?

The data includes market segments attributed as Unqualified and Qualified Non-block (excluding those with a Forecast Type Attributes of None).

In this example captured in March 2022, look at the forecast for the first quarter of 2023 (number 1). There are no On Books and the matching 2021 season is grayed out and excluded. Therefore, G3 RMS uses the demand level and trend from the same season in 2022 (number 2). Lowest in January, increasing in February and in March (arrows).

To keep it simple we only show the property level, but always verify at Forecast Group level! The patterns might look very different at the Forecast Group level, see the Day of Week Patterns example.

Recent Trends versus Similar Period in the Past

This example also shows how past seasonal trends might not be representative of current demand or the past data is excluded. In this case, due to COVID-19, the system might rely more on recent demand trends. Look at the forecast for April 2022 (number 3). The matching historical data, April 2021 and 2020, is excluded. Recent On Books is trending upwards since early February 2022 (number 2 and arrow). G3 RMS follows that trend and expects strong demand in April 2022, with many dates with unconstrained demand above capacity.

In this example we zoomed in to see the day of week pattern. At the property level the occupancy increases from the low on Sunday, slight decreases for Wednesday and Thursday and peaks on Friday and Saturday.

But G3 RMS forecasts at the Forecast Group (and Room Class) level, and at that level you see differences. For example, for a corporate Forecast Group, demand is highest on the Tuesday, then decreases.

These examples are for a period that is almost a year into the future. With no or very little On Books (1, 2, and 3) the patterns look very similar for multiple weeks. Where more On Books exist (arrow), the system varies the forecasts. And if On Books are stronger than the system expected, it might interpret that as stronger demand and increase the forecast.

Patterns can vary for repeat Special Events because G3 RMS uses the patterns of the last occurrence to forecast the next one. In this holiday example, December 21 to 25 is set up as a four-day Special Event. The following shows last year's occurrence when December 24, a Saturday, had higher demand than the other three days.

In the next, upcoming year, visual the green line shows that G3 RMS forecasts the same strong demand for December 24. But this year that date falls on a Friday and the demand for Saturday, December 25, might follow the normal day-of-week patterns and be stronger. If so, adjust the Special Event or override demand.

Look at the below scenario, step one. You might ask why the orange Occupancy Forecast for this Room Class is so high, close to capacity. And why the green System Total Demand is below the Occupancy Forecast. Step 2 shows that in the past, Demand for that Room Class was well below capacity.

To explain, we switch from Booked to Stayed. In step 3 we see that final Occupancy On Books for this Room Class was usually close to capacity. This is due to upgrades, enabled by Room Type Overbooking and the Upgrade Path. The difference between System Total Demand and Occupancy Forecast is because G3 RMS expects upgrades in the future too.